1. Field of the Invention
The present invention relates to an information processing apparatus, an information processing method, a computer program, and recording medium, and, more particularly to an information processing apparatus, an information processing method, a computer program, and a recording medium suitably used in detecting the motion of an object.
2. Description of the Related Art
Various methods have been used to acquire moving image data and detect the motion of an object.
There are proposed a large number of methods of identifying, from acquired moving image data, positions of specific body parts such as hands and feet of an object, which should be recognized, and recognizing actions from motion information of the body parts. Specifically, there are, for example, a method of using special equipment for identifying body parts (see, for example, Japanese Patent No. 2558943or Japanese Patent No. 3144400), a method of performing template matching (see, for example, Japanese Patent No. 2781743 or JP-A-8-279044), and a method of identifying body parts using color information or contour information (see, for example, U.S. Pat. No. 625,600B1, Japanese Patent No. 2868449, Japanese Patent No. 2934190, Japanese Patent No. 3440644, JP-A-10-214346, JP-A-2003-039365, JP-A-2003-216955, or Japanese Patent No. 2868449).
There is also proposed a method of extracting a motion area according to temporal subtraction or optical flow and recognizing actions from a center-of-gravity temporal change pattern of the area (see, for example, U.S. Pat. No. 6,681,031B2)).
There is also proposed a method of preparing, for an action desired to be recognized (a model action), a large amount of motion images for learning in which the action is imaged, extracting a feature quantity group that describes space-time events from the respective moving images, and performing learning using a statistical learning method such as a support vector machine to thereby obtain feature quantities for satisfactorily separating the model action from other space-time patterns out of the feature quantity group, and, in recognizing the model action from an input moving image during recognition processing, judging presence or absence of detection using only the feature quantity obtained by the learning (see, for example, C. Schuldt, I. Laptev, and B. Caputo, Recognizing human actions: a local SVM approach, In ICPR, pages III: 3236, 20).